Remote sensing technologies are used to measure electromagnetic radiation as reflected from objects to observe the object's physical properties. Remote sensing allows for the identification of materials and their composition. The measurements are typically acquired by spaceborne, airborne, handheld, or underwater sensor technologies.
Typically, the Sun is the electromagnetic radiation source whose energy is reflected by the object, and collected and measured by passive sensing instruments. In one approach for multispectral remote sensing, narrowband filters are applied over an array of sensors to detect the reflectance of an object as a function of optical wavelength in tens of spectral bands. Different materials have distinct reflectance values in different spectral bands and specific wavelengths. For example, in the detection and identification of minerals, by observing the reflectance of a material in different wavelengths, the reflectance from the material can be compared to the known spectral signatures of certain minerals to identify the presence of the mineral in the material.
One disadvantage of measuring the Sun's reflected energy in remote sensing is the effect of the Earth's atmosphere on the solar blackbody spectrum. Atmospheric gases, such as water vapor, carbon dioxide, and ozone, absorb radiation and limit the electromagnetic wavelengths available for terrestrial and aquatic remote sensing. Any such solar radiation will have first traveled through the atmosphere once to reach the target, be reflected, and traveled through the atmosphere again before reaching the sensing instrument, with sufficient amounts of the radiation absorbed by the atmosphere to affect the accuracy of the measurement of the reflectance in nontrivial ways. This phenomenon is compounded by water column absorption in the case of aquatic remote sensing, limiting the Sun's penetration depth to the top 100 meters in the ocean, for example. Other objects in the atmosphere and water column can also affect the transmission of the radiation in unpredictable ways. Accordingly, atmospheric and water column calibrations are required to estimate the interference and reverse the effects of the atmosphere and water column on the Sun's reflected light rays.
Hyperspectral remote sensing similarly observes the Sun's reflected radiation, but uses photodetectors and scanning spectrometers to resolve hundreds or even thousands of spectral bands. Even with this enhancement, passive remote sensing techniques remain limited by the ambient conditions along the optical path, by the ambient illumination spectrum, and hardware limits in optical aperture, and optical signal-to-noise ratio. Consequently, long integration times are necessary to collect the photons necessary for nocturnal and deep sea remote sensing.
Active remote sensing technologies using radio waves (Radio Detection and Ranging [RADAR]) and lasers (Light Detection and Ranging [LiDAR]) allow for remote sensing largely independent of ambient illumination conditions. Such approaches provide sufficient transmitter power over the background irradiance, and exploit phase information to overcome attenuation and distortion along the optical path. As such, receiver requirements in sensitivity, aperture, and signal-to-noise ratio are mitigated by transmitter power when using RADAR and LiDAR for active remote sensing applications. However, active remote sensing using RADAR and LiDAR cannot provide the visual images and wavelength-dependent reflectance information captured in passive remote sensing techniques across the full visible optical spectrum. Finally, materials can exhibit complex optical properties such as polarization-dependent reflectance and non-linear reflectance that can further be used to identify material properties and constituents.
It would be desired to provide a system and method for active multispectral or hyperspectral imaging, detection, and non-linear reflectance that overcomes the disadvantages described above.